Improving process and enhancing parent and therapist satisfaction through a coordinated intake approach
Bibliographic record
Abstract
Recent research indicates that, in Canada, approximately one in five children entering school are not meeting age appropriate milestones in physical, social, language, or cognitive development. Even where support services are available families often face barriers in accessing these. With the goals of improving access to programs, reducing barriers and increasing consistency and efficiency, a new Coordinated Intake Approach (CIA) was developed for families accessing Children’s Rehabilitation Services. It was expected that the CIA would result in 1) parents finding the intake process more satisfactory and easier to complete, 2) therapists feeling more supported and satisfied and 3) a decrease in wait times from the date referrals were received to initial contact with families. Initial data was collected prior to CIA implementation through parent telephone interviews and therapist surveys. This data was then compared with telephone interviews, therapist surveys and chart reviews completed following implementation. Results were consistent with expectations, suggesting that a family centered, CIA contributed to increased parent and therapist satisfaction as well as improved process efficiency. CIA successes and areas for improvement are identified. Possible directions for further process enhancements are also discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".